Basic Tree Stats

Project Description

In this project, I will be using tree inventory data from Ottawa Open Data to practice data analysis and data visualization work in Python.

Contains information licensed under the Open Government Licence – City of Ottawa

import requests
import pandas as pd
import plotly.express as px

# Eventually add some logic for full data fetching via API, 1000 limit right now
url = "https://maps.ottawa.ca/arcgis/rest/services/Forestry/MapServer/0/query?outFields=*&where=1%3D1&f=geojson"
resp = requests.get(url)
print(resp.status_code)

200

trees = pd.json_normalize(resp.json()['features'])
trees.columns = trees.columns.map(lambda x: x.split(".")[-1])
trees["species_general"] = trees["SPECIES"].str.split(" ").str[0]
trees.head()

	type	id	type	coordinates	OBJECTID	WARD	ADDNUM	ADDSTR	LTLOCATION	RDLOCATION	...	EDGETREE	PATHTRAIL	SPECIES	DBH	TREATMENT	EABTAGNUMBER	DEDTAGNUMBER	SAP_ID	PROGRAM	species_general
0	Feature	63887	Point	[-75.6813293769492, 45.431577387384344]	63887	12	151	CHAPEL ST	Front	N/A	...	0	0	Linden Littleleaf	45.0	None	None	None	8113295	None	Linden
1	Feature	63888	Point	[-75.68128713726621, 45.43137388688068]	63888	12	151	CHAPEL ST	Front	N/A	...	0	0	Maple Manitoba	66.0	None	None	None	8113293	None	Maple
2	Feature	63889	Point	[-75.68140123408709, 45.43136945702825]	63889	12	151	CHAPEL ST	Front	N/A	...	0	0	Maple Manitoba	62.0	None	None	None	8113292	None	Maple
3	Feature	63890	Point	[-75.6811069981023, 45.43111744784172]	63890	12	153	CHAPEL ST	Front	N/A	...	0	0	Linden Littleleaf	26.0	None	None	None	8113306	None	Linden
4	Feature	63891	Point	[-75.68098576955637, 45.43104793782418]	63891	12	153	CHAPEL ST	Front	N/A	...	0	0	Linden Littleleaf	31.0	None	None	None	8113305	None	Linden

5 rows × 21 columns

species_ward_count = pd.DataFrame({'count' : trees.groupby(["species_general", "WARD"])["species_general"].count()}).reset_index()
species_ward_count

fig = px.bar(species_ward_count, x="WARD", y="count", color="species_general", title="Species by Ward")
fig.show()